I. Technical Field of the Invention
The present invention is related to binarization schemes and coding schemes, in general, and in particular, to binarization and arithmetic coding schemes for use in video coding applications.
II. Description of the Prior Art
Entropy coders map an input bit stream of binarizations of data values to an output bit stream, the output bit stream being compressed relative to the input bit stream, i.e., consisting of less bits than the input bit stream. This data compression is achieved by exploiting the redundancy in the information contained in the input bit stream.
Entropy coding is used in video coding applications. Natural camera-view video signals show non-stationary statistical behavior. The statistics of these signals largely depend on the video content and the acquisition process. Traditional concepts of video coding that rely on mapping from the video signal to a bit stream of variable length-coded syntax elements exploit some of the non-stationary characteristics but certainly not all of it. Moreover, higher-order statistical dependencies on a syntax element level are mostly neglected in existing video coding schemes. Designing an entropy coding scheme for video coder by taking into consideration these typical observed statistical properties, however, offer significant improvements in coding efficiency.
Entropy coding in today's hybrid block-based video coding standards such as MPEG-2 and MPEG-4 is generally based on fixed tables of variable length codes (VLC). For coding the residual data in these video coding standards, a block of transform coefficient levels is first mapped into a one-dimensional list using an inverse scanning pattern. This list of transform coefficient levels is then coded using a combination of run-length and variable length coding. The set of fixed VLC tables does not allow an adaptation to the actual symbol statistics, which may vary over space and time as well as for different source material and coding conditions. Finally, since there is a fixed assignment of VLC tables and syntax elements, existing inter-symbol redundancies cannot be exploited within these coding schemes.
It is known, that this deficiency of Huffman codes can be resolved by arithmetic codes. In arithmetic codes, each symbol is associated with a respective probability value, the probability values for all symbols defining a probability estimation. A code word is coded in an arithmetic code bit stream by dividing an actual probability interval on the basis of the probability estimation in several sub-intervals, each sub-interval being associated with a possible symbol, and reducing the actual probability interval to the sub-interval associated with the symbol of data value to be coded. The arithmetic code defines the resulting interval limits or some probability value inside the resulting probability interval.
As may be clear from the above, the compression effectiveness of an arithmetic coder strongly depends on the probability estimation and the symbols, which the probability estimation is defined on. The symbols may be the data values in the input bit stream or the syntax elements in the input bit stream. In this case, the binarization of the data values is not critical.